BIT-PARALLEL COMPUTATION OF LOCAL SIMILARITY SCORE MATRICES WITH UNITARY WEIGHTS

Local similarity computation between two sequences permits detecting all the relevant alignments present between subsequences thereof. A well-known dynamic programming algorithm works in time O(mn), m and n being the lengths of the subsequences. The algorithm is rather slow when applied over many sequence pairs. In this paper we present the first bit-parallel computation of the score matrix, for a simplified choice of scores. If the computer word has w bits, then the resulting algorithm works in O(mn log min (m, n, w)/w) time, achieving up to 8-fold speedups in practice. Some DNA comparison applications use precisely the simplified scores we handle, and thus our algorithm is directly applicable. In others, our method could be used as a raw filter to discard most of the strings, so the classical algorithm can be focused only on the substring pairs that can yield relevant results.